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classifier.train(); |
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classifier.addImage(puffinImage1, 'Puffin');classifier.addImage(puffinImage1, 'Puffin'); | |
classifier.addImage(puffinImage2, 'Puffin');classifier.addImage(puffinImage2, 'Puffin'); | |
classifier.addImage(puffinImage3, 'Puffin');classifier.addImage(puffinImage3, 'Puffin'); | |
classifier.addImage(snowLeopardImage1, ‘Snow Leopard’);classifier.addImage(snowLeopardImage1, ‘Snow Leopard’); | |
classifier.addImage(snowLeopardImage2, ‘Snow Leopard’);classifier.addImage(snowLeopardImage2, ‘Snow Leopard’); |
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const classifier = features.classification(); |
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let features = ml5.featureExtractor('MobileNet'); |
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classifier.predict(gotResult); | |
function gotResult(results) { | |
console.log(results); | |
} |
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let video = createCapture(VIDEO); | |
let classifier = ml5.imageClassifier('MobileNet', video); |
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let classifier = new ml5.ImageClassifier('MobileNet'); |
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# the following two lines give a two-line status, with the current window highlighted | |
hardstatus alwayslastline | |
hardstatus string '%{= kG}[%{G}%H%? %1`%?%{g}][%= %{= kw}%-w%{+b yk} %n*%t%?(%u)%? %{-}%+w %=%{g}][%{B}%m/%d %{W}%C%A%{g}]' | |
# huge scrollback buffer | |
defscrollback 5000 | |
# no welcome message | |
startup_message off |
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var scene, | |
camera, | |
light, | |
renderer, | |
timer, | |
manager; | |
function init(){ | |
manager = new THREE.LoadingManager(); | |
//Don't start rendering until you finish loading |
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